Evidence map›Paper›PMID 39838499›Full record

ArticleBMC research notes2025

Measuring social integration, treatment, and mortality after substance use treatment: methodological elaborations in a 20-year follow-up study.

Tove Sohlberg, Jessica Storbjörk, Peter Wennberg

Abstract read
In one paragraph

Article in BMC research notes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Tove SohlbergDepartment of Public Health Sciences, Stockholm University, Stockholm, Sweden.ORCID http://orcid.org/0000-0003-2459-1311
Jessica StorbjörkDepartment of Public Health Sciences, Stockholm University, Stockholm, Sweden. jessica.storbjork@su.se.ORCID http://orcid.org/0000-0002-1757-9974
Peter WennbergDepartment of Public Health Sciences, Stockholm University, Stockholm, Sweden.ORCID http://orcid.org/0000-0002-0013-2965

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveAlcohol and Other Drug (AOD) disorders cause substantial harm. Effective Substance Use Treatment (SUT) exists, but long-term outcomes remain inconclusive. This study used a 20-year prospective follow-up of 1248 service users entering SUT in Stockholm, Sweden, in 2000-2002 to elaborate on how different dimensions of long-term outcomes may be measured by register-based indicators. Baseline characteristics and attrition bias were explicated, and register-based outcomes were examined.

resultsRegister-based indicators are valuable, but they also have inherent limitations such as the lack of substance use data and inability to differentiate between un/met treatment needs and access. Significant variations in long-term outcomes were evident depending on which register-based indicator was used, and whether used in isolation or combinations. Six out of 10 service users were still alive after 20 years, but as many as 8 out of 10 of the survivors remained in treatment, and only two out of 10 had a stable economic situation. Hence, the register indicators identified only a few survivors, with stable economic and social situations, and without recent treatment contacts 20 years after treatment entry. The long-term outcomes were concerning and even more so when combining outcome dimensions.

Indexed as

Substance-Related DisordersAdultFemaleFollow-Up StudiesHumansMaleMiddle AgedProspective StudiesRegistriesSwedenTreatment OutcomeAlcoholDrugsLong-term outcomesSubstance use treatmentSweden

Identifiers

PMID39838499
PMCPMC11749105

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.